Revealing the dynamic modularity of composite biological networks in breast cancer treatment

• Published in: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2012; pp. 5432 - 5436
• Main Authors: Dimitrakopoulou, K., Dimitrakopoulos, G., Zacharaki, E. I., Maraziotis, I. A., Sgarbas, K., Bezerianos, A.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2012
• Subjects: Algorithm design and analysis; Antineoplastic Agents, Hormonal - therapeutic use; Breast Neoplasms - drug therapy; Breast Neoplasms - genetics; Breast Neoplasms - metabolism; Breast Neoplasms - pathology; Female; Gene expression; Humans; Indexes; Lead; Measurement; Proteins; Proteome; Tamoxifen - therapeutic use; Transcriptome
• ISBN: 1424441196; 9781424441198
• ISSN: 1094-687X; 1557-170X; 1558-4615
• DOI: 10.1109/EMBC.2012.6347223

A major challenge in modern breast cancer treatment is to unravel the effect of drug activity through the systematic rewiring of cellular networks over time. Here, we illustrate the efficacy and discriminative power of our integrative approach in detecting modules that represent the regulatory effect of tamoxifen, widely used in anti-estrogen treatment, on transcriptome and proteome and serve as dynamic sub-network signatures. Initially, composite networks, after integrating protein interaction and time series gene expression data between two conditions (estradiol and estradiol plus tamoxifen), were constructed. Further, the Detect Module from Seed Protein (DMSP) algorithm elaborated on the graphs and constructed modules, with specific `seed' proteins used as starting points. Our findings provide evidence about the way drugs perturb and rewire the high-order organization of interactome in time.